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Yan Liu
Research Staff Member Data Analytic Group IBM T.J. Watson Research Center
Email:removeityanliuremoveit@cs.cmu.edu |
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I was a PhD student at Language
Technologies Institute, a part of School
of Computer Science in Carnegie Mellon
University working with Prof Jaime
Carbonell. I am currently a research staff member in the Data
Analytic Group in IBM T.J.
Watson Research Center.
Research Interest
I am interested in developing machine learning and data mining algorithms with applications to business intelligence, computational biology, information retrieval and natural language processing.
Publications
2007
· A. Arnold, Y. Liu, N. Abe. Temporal Causal Modeling with Graphical Granger Methods. In proceedings of the Thirteenth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (SIGKDD-07), 2007. [PDF]
· S. Rosset, C. Perlich, Y. Liu. Making the Most of Your Data: KDD Cup 2007 "How Many Ratings" Winners Report. In proceedings of KDD Cup and Workshop 2007. First place for KDD Cup 2007 of Netflix “How Many Ratings in 2006” task. [PDF]
· Y. Liu, Z. Kou. Predicting Who Rated What in Large-Scale Datasets. In proceedings of KDD Cup and Workshop 2007. Second Runner-up for KDD Cup 2007 of Netflix “Who Rated What in 2006” task. [PDF]
· M. Helander, R. Lawrence, Y. Liu, C. Perlich, C. Reddy, S. Rosset. Looking for Great Ideas: Analyzing the Innovation Jam. In proceedings of KDD Workshop on Web Mining and Social Network Analysis, 2007. [PDF]
· P. Melville, Y. Liu, R. Lawrence, I. Khabibrakhmanov, C. Pendus, T. Bowden. Finding New Customers Using Unstructured and Structured Data. In proceedings of KDD Workshop on Web Mining Multiple Information Sources, 2007. [PDF]
· J. Yang, Y. Liu, E. P. Xing, A. Hauptmann. Harmonium Models for Semantic Video Representation and Classification. In SIAM Conf. on Data Mining 2007, Minneapolis, Minnesota, Apr. 26-28, 2007. Winner of the Best Application Paper Award [PDF]
· Y. Liu, J G. Carbonell, V. Gopalakrishnan, P. Weigele. Protein Quaternary Fold Recognition Using Conditional Graphical Models. International Joint Conference in Artificial Intelligence (IJCAI-07) [PDF]
· J. He, J. Carbonell, Y. Liu. Graph-Based Semi-Supervised Learning as a Generative Model. International Joint Conference in Artificial Intelligence (IJCAI-07), 2007 [PDF]
· K. Probst, R. Ghani, M. Krema, A. Fano, Y. Liu. Semi-supervised Learning of Attribute-Value Pairs from Product Descriptions. International Joint Conference in Artificial Intelligence (IJCAI-07) [PDF]
2006
· R. Ghani, K. Probst, Y. Liu, M. Krema, and A. Fano. Text Mining to Extract Product Attributes. SIGKDD Explorations (2006) [PDF]
· Y. Liu, J. Carbonell, P. Weigele, V. Gopalakrishnan. Protein Fold Recognition Using Segmentation Conditional Random Fields (SCRFs). Journal of Computational Biology [PDF]
2005
· Y. Liu, E. P. Xing, J. Carbonell. Predicting Protein Folds with Structural Repeats Using a Chain Graph Model. International conference on Machine Learning (ICML’05), 2005 [PDF]
· Y. Liu, J. Carbonell, P. Weigele, V. Gopalakrishnan. Segmentation Conditional Random Fields (SCRFs): A New Approach for Protein Fold Recognition. International conference on Research in Computational Molecular Biology (RECOMB’05), 2005 [PDF]
2004
· J. Lafferty, X. Zhu, Y. Liu. Kernel Conditional Random Fields: Representation and Clique Selection. International Conference on Machine Learning (ICML'04), 2004 [PDF]. An earlier version of the paper can be found in CMU technical report CMU-CS-04-115, 2004.
· Y. Liu, J. Carbonell, J. Klein-Seetharaman, V. Gopalakrishnan. Comparison of Probabilistic Combination Methods for Protein Secondary Structure Prediction. Bioinformatics. 2004 Nov 22;20(17):3099-107 [PDF]
· Y. Liu, J. Carbonell, J. Klein-Seetharaman, V. Gopalakrishnan. Context Sensitive Vocabulary and Its Application in Protein Secondary Structure Prediction. International Conference on Research and Development in Information Retrieval (SIGIR'04), 2004. (Poster) [PDF]
2003 and earlier
· R. Jin, Y. Liu, S. Luo, J. Carbonell and A. Hauptmann. A New Boosting Algorithm Using Input-Dependent Regularizer. International Conference on Machine Learning (ICML'03), 2003 [PDF]
· Y. Liu, J. Carbonell and R. Jin. A New Pairwise Ensemble Approach for Text Classification. European Conference on Machine Learning (ECML'03), 2003 [PDF]
· R Yan, Y. Liu, R. Jin and A. Hauptmann. On Predicting Rare Class with SVM Ensemble in Scene Classification. IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2003), Hong Kong, China, April 6-10, 2003 [PDF]
· Y. Liu, Y, Yang and J. Carbonell. Boosting to Correct the Inductive Bias for Text Classification. ACM International Conference on Information and Knowledge Management (CIKM’02), Nov 4 - Nov 9, 2002 [pdf]